- Save the model based on the best metric, such as validation accuracy or validation loss, at different points in training.pythonCopy code
from tensorflow.keras.callbacks import ModelCheckpoint checkpoint = ModelCheckpoint('best_model.h5', monitor='val_accuracy', save_best_only=True, mode='max') model.fit(X_train, y_train, validation_data=(X_val, y_val), epochs=50, callbacks=[checkpo
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